Matlab Process Images

se = strel("sphere", 3);       % Sphere of radius 3
se = strel("cube", 5);         % 5×5×5 cube
se = strel("cuboid", [3 3 7]); % Anisotropic cuboid

voxelSize = [0.5 0.5 2.5];  % [row col slice] in mm
targetRadius = 2;  % mm
seSize = round(2*targetRadius ./ voxelSize);
seSize = seSize + (1 - mod(seSize, 2));  % Ensure odd
se = strel("cuboid", seSize);

cc = bwconncomp(bw3d, 6);           % Stricter separation
bw = bwvolumefilt(bw3d, 5, 6);      % 5 largest by volume, 6-connectivity

% Gaussian smoothing
smoothed = imgaussfilt3(V, sigma);            % Isotropic sigma
smoothed = imgaussfilt3(V, [sx sy sz]);       % Anisotropic sigma

% Median filtering
denoised = medfilt3(V);                       % Default 3×3×3
denoised = medfilt3(V, [3 3 5]);              % Anisotropic kernel

% Box filtering (fast mean)
mean3 = imboxfilt3(V, [3 3 3]);

% Custom 3-D kernel via imfilter 
h = fspecial3("gaussian", [7 7 7], 1.5);      
filtered = imfilter(V, h, "replicate");

% Anisotropic diffusion (edge-preserving)
% imdiffusefilt accepts 3-D grayscale volumes directly
denoised = imdiffusefilt(V);

% Mode filter for label/categorical volumes (preserves discrete values)
labelSmoothed = modefilt(labelVol, [3 3 3]);

% edge3 — threshold is REQUIRED (unlike 2-D edge which auto-computes)
BW = edge3(V, "approxcanny", 0.5);              % Scalar threshold
BW = edge3(V, "approxcanny", [0.2 0.5]);        % [low high] thresholds
BW = edge3(V, "approxcanny", [0.2 0.5], 1.5);   % With sigma

BW = edge3(V, "Sobel", 0.3);                    % Sobel method

% imgradient3 — gradient magnitude and direction (not binary edges)
[Gmag, Gazimuth, Gelevation] = imgradient3(V);

% imadjustn — N-D equivalent of imadjust
Vadj = imadjustn(V);                          % Auto stretch to [0 1] output
Vadj = imadjustn(V, stretchlim(V(:)));        % Percentile-based limits

% N-D histogram matching (align intensities to a reference volume)
Vmatched = imhistmatchn(V, Vref);
Vmatched = imhistmatchn(V, Vref, 128);        % Custom bin count

% Per-slice CLAHE (adapthisteq is 2-D only)
Vclahe = zeros(size(V), "like", V);
for k = 1:size(V, 3)
    Vclahe(:,:,k) = adapthisteq(V(:,:,k));
end

BW = imbinarize(V);                                % Otsu on 3-D grayscale
BW = imbinarize(V, "adaptive", Sensitivity=0.5);   % Adaptive on 3-D volume

% Or via adaptthresh (equivalent — build threshold volume explicitly)
T = adaptthresh(V, 0.5);
BW = imbinarize(V, T);

se = strel("sphere", 2);
bw = imbinarize(V);                  % Otsu on volume
bw = imopen(bw, se);                 % Remove small protrusions
bw = imclose(bw, se);                % Fill small gaps
bw = imfill(bw, "holes");            % Fill fully-enclosed 3-D holes
bw = imclearborder(bw);              % Remove objects touching any volume face
bw = bwareaopen(bw, minVoxelCount);  % Remove small objects by voxel count

% Filter by volume (3-D equivalent of bwareafilt)
bwFiltered = bwvolumefilt(bw, [minVol maxVol]);           % Keep objects in volume range
bwFiltered = bwvolumefilt(bw, n);                          % Keep n largest objects (default)
bwFiltered = bwvolumefilt(bw, n, "smallest");              % Keep n smallest
bwFiltered = bwvolumefilt(bw, n, 6);                       % With explicit connectivity

% Filter by any regionprops3 property (3-D equivalent of bwpropfilt)
bwFiltered = bwpropfilt3(bw, "SurfaceArea", [100 Inf]);
bwFiltered = bwpropfilt3(bw, "Solidity", 3, "largest");
bwFiltered = bwpropfilt3(bw, I, "MeanIntensity", [50 200]);   % Needs grayscale I

% Both accept a connected component structure (from bwconncomp) as input:
cc = bwconncomp(bw, 6);
ccFiltered = bwpropfilt3(cc, "Volume", [1000 Inf]);

cc = bwconncomp(bw, 26);
props = regionprops3(cc, "Volume", "Centroid");

keep = props.Volume > minVolume;
L = labelmatrix(cc);
bwFiltered = ismember(L, find(keep));

% Multiple properties
keep = props.Volume > 100 & props.Volume < 10000;
bwFiltered = ismember(L, find(keep));

props = regionprops3(cc, "Volume", "Centroid", "PrincipalAxisLength", "SurfaceArea");

props = regionprops3(cc, V, "MeanIntensity", "MaxIntensity", "MinIntensity", "VoxelValues", "WeightedCentroid");

% Distance-transform based (for separating touching convex objects)
D = bwdist(~bw);
D = -D;
D = imhmin(D, 2);      % Suppress shallow minima to reduce over-segmentation
L = watershed(D);
bwSeparated = bw & (L > 0);  % Watershed lines are L==0

D = imhmin(D, 2, 6);   % Stricter minima connectivity in 3-D

% Initial mask (rough estimate of region)
mask = false(size(V));
mask(r1:r2, c1:c2, s1:s2) = true;

% Chan-Vese (region-based, no edge needed) — default method
result = activecontour(V, mask, numIterations, "Chan-Vese");

% Edge-based
result = activecontour(V, mask, numIterations, "edge");

W = graydiffweight(V, seedCol, seedRow, seedSlice);       % Intensity-difference weights
BW = imsegfmm(W, seedCol, seedRow, seedSlice, 0.01);     % Geodesic threshold

W = gradientweight(V);                                    % Gradient-based weights
BW = imsegfmm(W, seedCol, seedRow, seedSlice, 0.05);

Vs = imresize3(V, 0.5);                          % Uniform scale
Vs = imresize3(V, [200 200 100]);                % Explicit output size
Vs = imresize3(V, [200 200 100], "nearest");     % Preserve labels/masks

Vr = imrotate3(V, 30, [0 0 1]);                          % 30° about Z
Vr = imrotate3(V, 45, [1 1 0], "linear", "crop");        % 45° about [1 1 0], cropped to input size
Vr = imrotate3(V, 15, [1 0 0], FillValues=NaN);          % NaN fill (FillValues must be numeric)

Vc = imcrop3(V, [xmin ymin zmin width height depth]);

[B, x, y, z] = obliqueslice(V, [cx cy cz], [nx ny nz]);  % Center point + normal vector
B = obliqueslice(V, center, normal, Method="nearest");     % For label volumes

% 3-D affine transform (12 DOF)
A = [1 0 0 tx; 0 1 0 ty; 0 0 1 tz; 0 0 0 1];   % Translation example
tform = affinetform3d(A);

% Rigid: Euler angles + translation
tform = rigidtform3d(eulerAngles, [tx ty tz]);

% Warp with spatial referencing (critical for anisotropic voxels)
Rin  = imref3d(size(V), voxSpacing(2), voxSpacing(1), voxSpacing(3));  % x,y,z
Vw   = imwarp(V, Rin, tform, OutputView=Rin);
Vw   = imwarp(V, Rin, tform, "nearest");  % For label/mask volumes

voxelSize = [0.5 0.5 2.5];        % [row col slice] mm
targetSpacing = min(voxelSize);   % Resample to finest dimension
scale = voxelSize / targetSpacing;
newSize = round(size(V) .* scale);
Viso = imresize3(V, newSize, "linear");

maskIso = imresize3(uint8(mask), newSize, "nearest") > 0;
% Or, for a categorical label volume:
labelsIso = imresize3(labelsCategorical, newSize, "nearest");

% Volume rendering
volshow(V);

% With label overlay
volshow(V, OverlayData=labelVol);

% Orthogonal slice planes through the volume
volshow(V, RenderingStyle="SlicePlanes");

% Isosurface extraction + display (modern: viewer3d + Surface)
viewer = viewer3d;
[faces, verts] = isosurface(V, isovalue);
tri = triangulation(faces, verts);
images.ui.graphics.Surface(viewer, Data=tri);

% Slice browsing
sliceViewer(V);              % Single-direction slice browser with slider
orthosliceViewer(V);         % Three orthogonal views with linked crosshairs

% All slices as tiled gallery
montage(V);